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<title>Reproducible Research: Peer Assessment 1</title>
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<h1>Reproducible Research: Peer Assessment 1</h1>
<hr/>
<h2>Loading and preprocessing the data</h2>
<p>Read in the data.</p>
<pre><code class="r">if (!file.exists("activity.csv")) {
unzip("activity.zip")
}
activity <- read.csv("activity.csv")
</code></pre>
<p>Create a date.time column that combines the date and interval columns.</p>
<pre><code class="r">time <- formatC(activity$interval/100, 2, format = "f")
activity$date.time <- as.POSIXct(paste(activity$date, time), format = "%Y-%m-%d %H.%M",
tz = "GMT")
</code></pre>
<p>For analyzing the means at the different times of day, it will also be convenient to have a time column. To do this, I convert all of the dates to be for today. since we only care about the time for that column, it will help us with the analysis.</p>
<pre><code class="r">activity$time <- format(activity$date.time, format = "%H:%M:%S")
activity$time <- as.POSIXct(activity$time, format = "%H:%M:%S")
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<p>First, calculate the mean number of steps for each day:</p>
<pre><code class="r">total.steps <- tapply(activity$steps, activity$date, sum, na.rm = TRUE)
</code></pre>
<p>Let's look at the mean and median for the total steps per day:</p>
<pre><code class="r">mean(total.steps)
</code></pre>
<p>[1] 9354</p>
<pre><code class="r">median(total.steps)
</code></pre>
<p>[1] 10395</p>
<p>And let's take a look at the distribution of total number of steps per day with a histogram:</p>
<pre><code class="r">library(ggplot2)
qplot(total.steps, xlab = "Total steps", ylab = "Frequency")
</code></pre>
<pre><code>## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.
</code></pre>
<p><img 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" alt="plot of chunk histogram"/> </p>
<h2>What is the average daily activity pattern?</h2>
<p>Calculate the mean steps for each five minute interval, and then put it in a data frame.</p>
<pre><code class="r">mean.steps <- tapply(activity$steps, activity$time, mean, na.rm = TRUE)
daily.pattern <- data.frame(time = as.POSIXct(names(mean.steps)), mean.steps = mean.steps)
</code></pre>
<p>Let's take a look at a time series plot for the mean steps.</p>
<pre><code class="r">library(scales)
ggplot(daily.pattern, aes(time, mean.steps)) + geom_line() + xlab("Time of day") +
ylab("Mean number of steps") + scale_x_datetime(labels = date_format(format = "%H:%M"))
</code></pre>
<p><img 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" alt="plot of chunk timeseriesplot"/> </p>
<p>Which five minute interval has the highest mean number of steps?</p>
<pre><code class="r">most <- which.max(daily.pattern$mean.steps)
format(daily.pattern[most, "time"], format = "%H:%M")
</code></pre>
<p>[1] “08:35”</p>
<h2>Imputing missing values</h2>
<p>Identify the number of intervals with missing step counts (“NA's”):</p>
<pre><code class="r">summary(activity$steps)
</code></pre>
<p>Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.0 0.0 0.0 37.4 12.0 806.0 2304 </p>
<p>To fill in the missing values, I'll use mean steps for a five-minute interval for the entire dataset.</p>
<pre><code class="r">library(Hmisc)
activity.imputed <- activity
activity.imputed$steps <- with(activity.imputed, impute(steps, mean))
</code></pre>
<p>Let's compare the mean and median steps for each day between the original data set and the imputed data set.</p>
<pre><code class="r">total.steps.imputed <- tapply(activity.imputed$steps, activity.imputed$date,
sum)
mean(total.steps)
</code></pre>
<p>[1] 9354</p>
<pre><code class="r">mean(total.steps.imputed)
</code></pre>
<p>[1] 10766</p>
<pre><code class="r">median(total.steps)
</code></pre>
<p>[1] 10395</p>
<pre><code class="r">median(total.steps.imputed)
</code></pre>
<p>[1] 10766</p>
<p>And a histogram of the imputed dataset.</p>
<pre><code class="r">qplot(total.steps.imputed, xlab = "Total steps", ylab = "Frequency")
</code></pre>
<pre><code>## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.
</code></pre>
<p><img 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" alt="plot of chunk histogram_imputed"/> </p>
<p>Imputing the missing data has increased the average number of steps. </p>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<p>Add a factor column for whether a day is a weekday or weekend.</p>
<pre><code class="r">day.type <- function(date) {
if (weekdays(date) %in% c("Saturday", "Sunday")) {
return("weekend")
} else {
return("weekday")
}
}
day.types <- sapply(activity.imputed$date.time, day.type)
activity.imputed$day.type <- as.factor(day.types)
</code></pre>
<p>Create a dataframe that holds the mean steps for weekdays and weekends.</p>
<pre><code class="r">mean.steps <- tapply(activity.imputed$steps, interaction(activity.imputed$time,
activity.imputed$day.type), mean, na.rm = TRUE)
day.type.pattern <- data.frame(time = as.POSIXct(names(mean.steps)), mean.steps = mean.steps,
day.type = as.factor(c(rep("weekday", 288), rep("weekend", 288))))
</code></pre>
<p>Now let's compare the patterns between weekdays and weekends.</p>
<pre><code class="r">ggplot(day.type.pattern, aes(time, mean.steps)) + geom_line() + xlab("Time of day") +
ylab("Mean number of steps") + scale_x_datetime(labels = date_format(format = "%H:%M")) +
facet_grid(. ~ day.type)
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk timeseries_daytype"/> </p>
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